Annals of Occupational and Environmental Medicine

Review

Factors associated with work-related musculoskeletal disorders using machine learning approaches: a systematic review: Muhammad Irfan Mohd Sallehhuddin, Siti Munira Yasin, Mohamad Rodi Isa, Tajul Rosli Razak, Muhamad Syazni Mohamad Asraff, Nur Adilla Che Rameli, Muhammad Muaz Shahriman-Teruna, Muhammad Muzzammil Mohamad Salleh, Mohamad Zuhair Mohamed Yusoff, Muhammad Hariz Ammar Khebir; Ann Occup Environ Med 2026;e10. Published online March 19, 2026; DOI: https://doi.org/10.35371/aoem.2026.38.e10 [Accepted]

Abstract PDF: Background
Work-related musculoskeletal disorders (WRMSDs) remain a major cause of occupational disability and productivity loss worldwide. Traditional statistical methods have identified numerous associated factors; however, they often struggle to capture complex non-linear relationships and interactions across multiple domains of risk. Machine learning (ML) offers an alternative analytical approach for modelling such multidimensional relationships.
Methods
Following the PRISMA 2020 guidelines (PROSPERO: CRD420250605234), literature searches were conducted in Web of Science, Scopus, and PubMed for studies published between 2020 and 2025. Eligible studies applied ML methods to identify factors associated with WRMSDs using cross-sectional study designs. Included studies were appraised using the Joanna Briggs Institute Critical Appraisal Checklist for analytical cross-sectional studies.
Results
Ten studies met the inclusion criteria, representing workers from healthcare, transport, manufacturing, and service sectors across Asia, Africa, and Europe. Frequently applied ML algorithms included random forest, support vector machine, and artificial neural networks, demonstrating strong internal discriminative performance (area under the receiver operating characteristic curve: 0.80–0.99), although the absence of external validation in several studies suggests a potential risk of overfitting. Commonly identified factors included age, sex, awkward posture, vibration exposure, prolonged working hours, stress, and burnout. Psychosocial factors, including post-traumatic stress disorder, job stress, and depression, were ranked among the most influential predictors within ML models.
Conclusions
ML models demonstrate strong capability in discriminating WRMSDs risk and identifying multidimensional risk factors compared with traditional statistical approaches. These models highlight complex interrelationships between ergonomic and psychosocial exposures. Future research should incorporate external validation, objective exposure measurements, and standardized ML reporting frameworks to enhance methodological transparency and generalizability.

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Original article

Occupational Diseases in Mongolia: A Retrospective Analysis (1975–2023) with a 30-Year Trend Study: Sansartsetseg Tsendjav, Myagmarchuluun Sainnyambuu, Otgonbayar Damdinbazar, Ulzii-Orshikh Ragchaabazar, Gantugs Yundendorj; Ann Occup Environ Med 2026;e12. Published online March 24, 2026; DOI: https://doi.org/10.35371/aoem.2026.38.e12 [Accepted]

Abstract PDF: Background
Occupational diseases represent a significant global public health challenge, yet reliable data from transitioning economies remain limited. This study aimed to analyze newly confirmed occupational disease cases in Mongolia over a 50-year period (1975–2023), identifying long-term trends and the prevalence of leading disease categories.
Methods
A retrospective, record-based study was conducted using quantitative data from 10,233 officially confirmed and compensated cases of occupational diseases resulting in an officially certified loss of labor capacity. Incidence rates per 100,000 workers were calculated for the 1992–2023 period. Leading diseases were classified by organ system, with focused analyses on respiratory diseases, occupational poisonings, and neurological disorders.
Results
Dust- and particulate-induced respiratory diseases accounted for the largest proportion of cases (57.3%), followed by occupational neurological disorders (16.2%) and occupational poisonings (7.9%). From 1992 to 2023, incidence rates among male workers were consistently 3–7 times higher than those among female workers. Analysis of exposure duration showed mean durations of 13.6 ± 4.9 years for silicosis (J62) and 20.7 ± 10.7 years for inorganic substance poisoning (T52). While respiratory diseases predominant historically, cases of occupational neurological diseases increased 1.9-fold after 2015.
Conclusions
Occupational neurological disorders are showing an increasing trend in Mongolia, reflecting a shift in the national occupational disease pattern. However, as the registry is based on the national compensation framework, these findings likely reflect recognized cases rather than the true epidemiological incidence, suggesting potential underreporting. Strengthening surveillance beyond the compensation system and improving diagnostic capacity for a broader range of work-related conditions are essential for effective prevention and policy development.

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Original Article

Risk of sleep disturbance associated with work-related activities during free time in South Korea: a cross-sectional study with mediation analysis: Ohwi Kwon, Hye-Eun Lee, Mo-Yeol Kang; Ann Occup Environ Med 2026;e11. Published online March 20, 2026; DOI: https://doi.org/10.35371/aoem.2026.38.e11 [Accepted]

Abstract PDF: Background
This study aims to investigate the associations between work-related activities during free time, including frequency of working during free time and use of communication devices for work during free time, and sleep disturbance. It further explores the underlying mechanisms through mediation analysis.
Methods
Data were analyzed from 21,473 participants of the seventh Korean Working Conditions Survey (KWCS, 2023). Multivariable logistic regression was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for sleep disturbance. Three sequential models were constructed to evaluate the effects of weekly working hours and shift work on sleep disturbance risk. Mediation analysis was conducted to identify pathways linking work-related activities during free time and sleep disturbance.
Results
Those who worked during their free time daily showed significantly higher risk of sleep disturbance (OR: 4.17; 95% CI: 2.64–6.58). Similarly, daily use of communication devices for work during free time was associated with an increased risk (OR: 1.83; 95% CI: 1.57–2.13). These associations remained robust even after adjusting for weekly working hours and shift work. Mediation analysis revealed that "worry about work while at home" was the primary mediator for device use (13.7%; 95% CI: 0.11–0.18), while "feeling too tired for housework after work" was the strongest mediator for working during free time (26.6%; 95% CI: 0.22–0.32).
Conclusions
The results indicate that engaging in work-related activities during free time elevates the risk of sleep disturbance, independent of long working hours or shift patterns. Mediation analysis revealed that the strongest effects were driven by the behavioral and psychological dimensions of work–family conflict. These findings suggest that sleep disturbance arises primarily from the erosion of work–life boundaries, fueled by persistent work-related rumination and the spillover of professional burdens into free time.

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Original Article

Association between working ≥10 hours per day and satisfaction with work environment among wage workers in Korea: a cross-sectional study using data from the 7th Korean Working Conditions Survey: Rae-Yun Kim, Dong-Woo Kim, Yoon-Soo Jang, Na-Rae Lee, June-Hee Lee, Kyung-Jae Lee; Ann Occup Environ Med 2026;e9. Published online March 18, 2026; DOI: https://doi.org/10.35371/aoem.2026.38.e9 [Accepted]

Abstract PDF: Background
Long working hours have been associated with adverse physical and mental health outcomes; however, evidence regarding their relationship with satisfaction with work environment remains limited, particularly when long working hours are defined using a specific daily threshold. This study examined the association between working ≥10 hours per day and satisfaction with work environment among Korean wage workers, focusing on the cumulative number of such workdays per month.
Methods
This cross-sectional study analyzed data from the 7th Korean Working Conditions Survey. A total of 24,269 wage workers aged ≥18 years were included after excluding self-employed workers, unpaid family workers, shift workers, and respondents with missing data. Working ≥10 hours per day was categorized as 0, 1–9, and ≥10 days per month. Satisfaction with work environment was categorized as satisfied or dissatisfied. Multiple logistic regression analyses were conducted to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for dissatisfaction with work environment according to the number of long working days, adjusting for demographic and occupational characteristics.
Results
Compared with workers who did not work ≥10 hours per day, those who worked 1–9 days and ≥10 days per month showed progressively higher levels of dissatisfaction with work environment. After adjustment for demographic and occupational factors, the odds of dissatisfaction with work environment were significantly higher among workers who worked ≥10 hours per day for 1–9 days per month (OR: 1.380; 95% CI: 1.145–1.665) and ≥10 days per month (OR: 2.106; 95% CI: 1.627–2.725), demonstrating a dose–response relationship.
Conclusions
Among the analytic sample of Korean wage workers included in this study, working ≥10 hours per day was associated with greater dissatisfaction with work environment, with a dose–response pattern according to the number of long working days per month.

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Case Report

Multiple chemical sensitivity triggered by an automobile mechanic's indirect exposure to volatile organic compounds in the Republic of Korea: a case report: Dong-Hoon Cheon, Yoon-Ji Kim, Dongmug Kang, Youngki Kim, Eun-Soo Lee, Ki-Hun Kim, Se-Yeong Kim; Ann Occup Environ Med 2026;e7. Published online February 26, 2026; DOI: https://doi.org/10.35371/aoem.2026.38.e7 [Accepted]

Abstract PDF: Background
Multiple chemical sensitivity (MCS) lacks definitive biomarkers, making differential diagnosis reliant on exclusion and symptom reproducibility. In automobile repair shops, volatile organic compounds (VOCs) from cleaning agents pose risks not only to primary users but also to co-workers via indirect exposure. We report a case of MCS suspected to be triggered solely by bystander VOC exposure, highlighting the clinical significance of uncaptured peak exposures in Korea.
Case presentation
A 23-year-old mechanic experienced recurrent headaches, throat irritation, and nausea immediately after co-workers used aerosolized cleaners in a poorly ventilated workspace. Symptoms consistently improved when he was away from work. Routine clinical evaluations were unremarkable. Although the patient underwent surgery for chronic rhinosinusitis, the symptoms persisted specifically upon re-exposure, effectively ruling out structural otorhinolaryngologic causes. Mental health screening indicated only mild depressive symptoms, insufficient to account for the severity of the physical symptoms. The Quick Environmental Exposure and Sensitivity Inventory (QEESI) scores were in the "suggestive" range for MCS. While routine workplace monitoring (8-hour time-weighted average [TWA]) showed non-detectable solvent levels, the nature of aerosol application suggested uncaptured short-term peak exposures. Based on the distinct temporal relationship, the patient was placed under medical observation and assessed as fit for work with restrictions on solvent exposure.
Conclusions
This case highlights the role of indirect VOC exposure as a trigger for MCS symptoms even when routine TWA monitoring indicates minimal concentrations. The discrepancy likely stems from the brief peak exposures triggering central sensitization, underscoring the limitations of standard monitoring. Management strategies must focus on peak-exposure control and fitness-for-work assessments that mandate strict avoidance of organic solvents, regardless of average ambient concentrations.

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